Item Recommendation Platform
(Redirected from Item(s) Recommendation Platform)
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An Item Recommendation Platform is an information filtering platform that can be used to implement an item(s) recommendation system (to solve an item(s) recommendation task).
- Context:
- It can range from being a Python-based Recommendation Platform, R-based Recommendation Platform, ..., Spark-based Recommender, ...
- It can be based on an Item(s) Recommendation Framework.
- Example(s):
- Counter-Example(s):
- …
- See: Personalized Item(s) Recommendations, Contextual Item(s) Recommendation.
References
2017
- https://github.com/ludovikcoba/rrecsys
- QUOTE: A package for R that provides implementations of several popular recommendation systems. They can process standard recommendation datasets (user/item matrix) as input and generate rating predictions and recommendation lists. Standard algorithm implementations included in this package are: Global/Item/User-Average baselines, Item-Based KNN, FunkSVD, BPR and weighted ALS. They can be assessed according to the standard offline evaluation methodology for recommender systems using measures such as MAE, RMSE, Precision, Recall, AUC, [[NDCG, RankScore and coverage measures. The package is intended for rapid prototyping of recommendation algorithms and education purposes.